> ## Documentation Index
> Fetch the complete documentation index at: https://docs.budecosystem.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quick Start

> Create an experiment and run your first model evaluation

This quick start shows the fastest path to run one evaluation and inspect results.

## Step 1: Open Evaluations

1. Sign in to Bud AI Foundry.
2. Go to **Evaluations** in the sidebar.
3. Keep the **Experiments** tab open for run management.

## Step 2: Create an Experiment

1. Click **New experiment**.
2. Enter:
   * **Name**: `Baseline Reasoning Comparison`
   * **Description**: `Compare candidate models on reasoning traits`
   * **Tags**: `baseline`, `reasoning`
3. Save the experiment.

<img src="https://mintcdn.com/budecosystem-b7b14df4/s1UIL561IqfFAT80/images/image-53.png?fit=max&auto=format&n=s1UIL561IqfFAT80&q=85&s=9dbcd71f428b2e78cb9b1485d557580a" alt="Image" width="1920" height="880" data-path="images/image-53.png" />

## Step 3: Start a Run

1. Open the experiment you created.
2. Click **Run Evaluation**.
3. Select:
   * A model (deployment or supported target)
   * One or more traits
   * Datasets mapped to those traits
4. Confirm and start the run.

```mermaid theme={null}
flowchart LR
    A[New Experiment] --> B[Run Evaluation]
    B --> C[Pick Model]
    C --> D[Pick Traits + Datasets]
    D --> E[Submit]
    E --> F[Run Queued/Running]
```

<img src="https://mintcdn.com/budecosystem-b7b14df4/s1UIL561IqfFAT80/images/image-56.png?fit=max&auto=format&n=s1UIL561IqfFAT80&q=85&s=eea79f8c9415df8afee0849cee0f799c" alt="Image" width="1920" height="876" data-path="images/image-56.png" />

<img src="https://mintcdn.com/budecosystem-b7b14df4/s1UIL561IqfFAT80/images/image-57.png?fit=max&auto=format&n=s1UIL561IqfFAT80&q=85&s=cb69517d43cf8f5156c1b16bfae738b9" alt="Image" width="1920" height="883" data-path="images/image-57.png" />

## Step 4: Monitor Progress

1. Watch run status in the experiment table.
2. Open run details to review:
   * Status and duration
   * Trait-level scores
   * Dataset-level benchmark summary

## Step 5: Compare and Decide

1. Open the dataset in **Evaluations Hub**.
2. Use **Leaderboard** for cross-model ranking.
3. Use **Evaluations Explorer** for prompt/response-level inspection.

<Tip>
  Use consistent experiment tags (for example: `release-candidate`, `nightly`) so filtering stays clean as runs scale.
</Tip>

## Next Steps

<CardGroup cols={2}>
  <Card title="Creating Your First Evaluation" icon="graduation-cap" href="/evaluations/creating-first-evaluation">
    Follow a production-style walkthrough
  </Card>

  <Card title="Troubleshooting" icon="wrench" href="/evaluations/troubleshooting">
    Resolve common run and filter issues quickly
  </Card>
</CardGroup>